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A TiNb2O7 anode material distributed in carbon-coated nanosheet arrays on carbon cloth is prepared by a facile method, and it is combined with LiNi0.5Mn1.5O4 to assemble full batteries with an improved energy density at high rates.

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Flavonoids are the main active ingredient in Citri Reticulatae Pericarpium Viride (CRPV).

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Species of the genus <i>Morchella</i> are highly prized worldwide for their excellent flavor and high medicinal value. In recent years, artificial cultivations of medicinal fungi with many advantages have elicited great interest as a promising alternative to produce certain valuable metabolites. Therefore, the secondary metabolites of fermented <i>M. importuna</i> belonging to the black morel clade isolated from China were investigated. The strain was cultured in a fermentation tank in PDB liquid medium by two-step method. The mycelia and fermentation broth were extracted by ethyl acetate. The secondary metabolites were separated and purified by repeated silica gel column chromatography. Structures of compounds were determined by NMR data and references. One new natural compound <b>(1)</b> and six known compounds <b>(2-7)</b> were obtained. Compounds<b> 1, 2, 4,</b> and<b> 5</b> were first isolated from genus <i>Morchella</i> and compounds<b> 3, 6,</b> and<b> 7</b> are first isolated from species <i>M. importuna</i>.

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Overlay multicast has become one of the most promising multicast solutions for IP network, and Neutral Network(NN) has been a good candidate for searching optimal solutions to the constrained shortest routing path in virtue of its powerful capacity for parallel computation. Though traditional Hopfield NN can tackle the optimization problem, it is incapable of dealing with large scale networks due to the large number of neurons. In this paper, a neural network for overlay multicast tree computation is presented to reliably implement routing algorithm in real time. The neural network is constructed as a two-layer recurrent architecture, which is comprised of Independent Variable Neurons (IDVN) and Dependent Variable Neurons (DVN), according to the independence of the decision variables associated with the edges in directed graph. Compared with the heuristic routing algorithms, it is characterized as shorter computational time, fewer neurons, and better precision.